The dynamic driving mechanisms of wetland change from an asynchrony-spatiotemporal perspective: A case study in Pearl River Delta, China

The mechanism of wetland distribution (WD) has been well studied, but further research is needed on the mechanism of wetland change (WC). This study developed a model of the impact of changes in human activity (HA) and natural environment factors on WC from an asynchronous–spatiotemporal perspective, integrating remote sensing technologies and partial least squares–structural equation modeling (PLS–SEM). In the model, HA was reflected by economic and population data. The natural environment was reflected by the fundamental natural environment (FNE), which was mainly based on terrain, and the non-stable natural environment (NNE), which was mainly based on hydrological and temperature conditions. The model met the accuracy requirements in the Pearl River Delta (PRD). The results showed that there were differences in the response of WD and WC to driving factors from 1980 to 2020 in the PRD. FNE had a negative impact on WD, however, FNE changes (FNEC) had a positive impact on WC (mainly wetlands decrease). HA could affect NNE and subsequently WD, but NNE changes (NNEC) only began to affect WC after 2010. HA had a negative impact on WD and WC from 1980 to 2010, but both negative and positive impacts existed after 2010. By coupling areas of HA changes (HAC) with wetland decrease, it was found that HA should be restricted in the southeast of Foshan (areas where HA increase led to wetland decrease) to protect wetlands; The junction between Zhaoqing and Foshan (areas where HA decrease lead to wetland decrease) requires investment in improving the natural environment. The model proposed in this study can be applied to other areas with severe wetland degradation from HA and natural conditions, to assist in local wetland restoration and management. • A dynamic driving mechanism model of wetland change was developed. • The asynchrony-spatiotemporal mechanisms were quantified based on the model. • The fundamental natural environment determines wetland distribution and limits human activities, protecting wetlands from damage. • The distribution of the impact of human activities on wetland loss was mapped.

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Publication Details

Journal
Ecological Informatics
Published
2024-12-27
DOI
https://doi.org/10.1016/j.ecoinf.2024.102979
Citations
2
Primary Topic
Coastal wetland ecosystem dynamics
Type
article
Field-Weighted Citation Impact
0.92
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article

The dynamic driving mechanisms of wetland change from an asynchrony-spatiotemporal perspective: A case study in Pearl River Delta, China

Haichao Zhou, Guangjia Jiang, Jiaojiao Ma, Zhongwen Hu et al.
2 citations
Ecological Informatics
Coastal wetland ecosystem dynamics
0.92
article

The dynamic driving mechanisms of wetland change from an asynchrony-spatiotemporal perspective: A case study in Pearl River Delta, China

Haichao Zhou, Guangjia Jiang, Jiaojiao Ma, Zhongwen Hu, Christian J. Sanders, Yuhang Wang, Wei Li, Xiaoqing Yi, Demin Zhou, Changjun Gao, Junjie Wang
article en
2 citations

Abstract

The mechanism of wetland distribution (WD) has been well studied, but further research is needed on the mechanism of wetland change (WC). This study developed a model of the impact of changes in human activity (HA) and natural environment factors on WC from an asynchronous–spatiotemporal perspective, integrating remote sensing technologies and partial least squares–structural equation modeling (PLS–SEM). In the model, HA was reflected by economic and population data. The natural environment was reflected by the fundamental natural environment (FNE), which was mainly based on terrain, and the non-stable natural environment (NNE), which was mainly based on hydrological and temperature conditions. The model met the accuracy requirements in the Pearl River Delta (PRD). The results showed that there were differences in the response of WD and WC to driving factors from 1980 to 2020 in the PRD. FNE had a negative impact on WD, however, FNE changes (FNEC) had a positive impact on WC (mainly wetlands decrease). HA could affect NNE and subsequently WD, but NNE changes (NNEC) only began to affect WC after 2010. HA had a negative impact on WD and WC from 1980 to 2010, but both negative and positive impacts existed after 2010. By coupling areas of HA changes (HAC) with wetland decrease, it was found that HA should be restricted in the southeast of Foshan (areas where HA increase led to wetland decrease) to protect wetlands; The junction between Zhaoqing and Foshan (areas where HA decrease lead to wetland decrease) requires investment in improving the natural environment. The model proposed in this study can be applied to other areas with severe wetland degradation from HA and natural conditions, to assist in local wetland restoration and management. • A dynamic driving mechanism model of wetland change was developed. • The asynchrony-spatiotemporal mechanisms were quantified based on the model. • The fundamental natural environment determines wetland distribution and limits human activities, protecting wetlands from damage. • The distribution of the impact of human activities on wetland loss was mapped.

Ecological InformaticsVol. 86
Shenzhen University (CN), Guangzhou Experimental Station (CN), Institute of Wetland Research (CN), Chinese Academy of Forestry (CN), Guangdong Province Environmental Monitoring Center (CN), Guangdong Academy of Forestry (CN), Southern Cross University (AU), Capital Normal University (CN)
Life below water
Openalex Percentile: Top 21%
Coastal wetland ecosystem dynamics
0.92
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